Modeling reveals metabolic basis of competition among <i>Dehalobacter</i> strains during tandem CF and DCM metabolism
Bibliographic record
Abstract
SC05-UT is an anaerobic mixed microbial enrichment culture that reduces chloroform (CF) to dichloromethane (DCM) through reductive dechlorination, which it further mineralizes to carbon dioxide. This DCM mineralization yields electron equivalents that are used to reduce CF without addition of exogenous electron donor. By studying this self-feeding CF-amended culture and a DCM-amended enrichment culture (DCME), we previously found the genomic potential to perform both biodegradation steps in two distinct Dehalobacter strains: Dehalobacter restrictus SAD and Candidatus Dehalobacter alkaniphilus DAD. Though present in each enrichment culture, strain SAD is more abundant in CF-fed subculture SC05-UT, while strain DAD is more prominent in the DCM-fed subculture DCME. To understand if genomic differences between strains and impact their metabolic mechanisms, the genome of each strain was curated to reconstruct genome-scale metabolic models of each strain, which were then constrained based on thermodynamic and experimental conditions. We demonstrate that metabolic differences between the two strains may allow Dehalobacter strain DAD to outcompete strain SAD in the absence of CF, while strain SAD exhibits an advantage in the presence of CF. Additionally, we predict electron cycling methods to reconcile redox imbalances in the cell is required for tandem CF and DCM dechlorination. This work highlights the importance of hydrogen and amino acid exchange in these microbial communities and contributes to the growing body of work surrounding organohalide syntrophy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".